Towards 360 VR Sickness Mitigation: From Virtual Reality Eye-tracking to Visual Communication

虚拟现实 计算机科学 模拟病 眼动 可视化 人机交互 数据可视化 多媒体 计算机视觉 视觉传达 计算机图形学(图像) 人工智能
作者
Jeonghaeng Lee,Woojae Kim,Chao Yang,Ping An,Sanghoon Lee
出处
期刊:IEEE Transactions on Visualization and Computer Graphics [Institute of Electrical and Electronics Engineers]
卷期号:: 1-13
标识
DOI:10.1109/tvcg.2024.3447838
摘要

Most 360 virtual reality (VR) contents have been developed without considering that users could be affected by VR sickness. Accordingly, users' viewing safety has been steadily highlighted as a critical problem in the VR market. In this study, we investigate a novel VR sickness mitigation framework based on human visual characteristics for the rendered VR content. First, we build a large-scale 360 VR content database termed VRSP360 (VR Sickness and Presence 360) dedicated to the analysis of VR sickness and thoroughly conduct eye-tracking experiments to measure human perception. In the experiment, we observe that the users' gaze distribution is highly center-biased when they experience excessive VR sickness. From this observation, we design a foveated filtering framework that limits high-frequency textures in the peripheral view to mitigate VR sickness. Particularly, given the human visual system's (HVS) non-uniform resolution with respect to the fovea, we also adopt the foveation-based filtering method using the trade-off between sickness mitigation and presence conservation, which reduces any loss in perceptual quality despite the filtering. We further demonstrate that our framework can effectively compress visual information by applying foveated compression. In addition, we develop two metrics (visual texture index and perceptual information index) to measure the effective preservation of user-perceived information despite the filtration of peripheral vision textures by our proposed mitigation method. Through rigorous subjective evaluation on both original content and its VR-sickness-mitigated version, we demonstrate that the proposed framework successfully mitigates VR sickness with a reduction rate of ∼ 19% on the proposed dataset.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
心系天下完成签到 ,获得积分10
1秒前
啧啧完成签到 ,获得积分10
6秒前
苏以禾完成签到 ,获得积分10
6秒前
桥豆麻袋完成签到,获得积分10
9秒前
9秒前
斯文败类应助科研通管家采纳,获得10
9秒前
CipherSage应助科研通管家采纳,获得10
9秒前
oc666888完成签到,获得积分10
10秒前
14秒前
杨洋完成签到 ,获得积分10
15秒前
yang完成签到 ,获得积分10
19秒前
小田完成签到 ,获得积分10
19秒前
念与惜完成签到 ,获得积分10
22秒前
小迪完成签到 ,获得积分10
36秒前
38秒前
江枫渔火完成签到 ,获得积分10
39秒前
nextconnie完成签到,获得积分10
41秒前
zbb123完成签到 ,获得积分10
45秒前
上官若男应助Laser_eyes采纳,获得10
46秒前
boymin2015完成签到 ,获得积分10
48秒前
50秒前
小包子完成签到,获得积分10
52秒前
homeless完成签到 ,获得积分10
55秒前
Stella完成签到 ,获得积分10
55秒前
sfliufighting发布了新的文献求助10
57秒前
曾经安萱完成签到,获得积分10
57秒前
牛仔完成签到 ,获得积分10
1分钟前
nono完成签到 ,获得积分10
1分钟前
vanliu完成签到,获得积分10
1分钟前
英俊的铭应助sfliufighting采纳,获得10
1分钟前
麦麦完成签到,获得积分10
1分钟前
咯咚完成签到 ,获得积分10
1分钟前
康家旗完成签到,获得积分10
1分钟前
qpzn完成签到,获得积分10
1分钟前
木雨亦潇潇完成签到,获得积分0
1分钟前
执着的天使完成签到 ,获得积分10
1分钟前
韩祖完成签到 ,获得积分10
1分钟前
春风完成签到 ,获得积分10
1分钟前
钰泠完成签到 ,获得积分10
1分钟前
刘一完成签到 ,获得积分10
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Adverse weather effects on bus ridership 500
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6350692
求助须知:如何正确求助?哪些是违规求助? 8165311
关于积分的说明 17182147
捐赠科研通 5406866
什么是DOI,文献DOI怎么找? 2862731
邀请新用户注册赠送积分活动 1840310
关于科研通互助平台的介绍 1689463